The Use of

Biometrics in Education

Technology Assessment

Authors:

Erica Frazier

Scott Greiner

Don Wethington

April 26, 2004

Introduction

    This technology assessment deals with the use of biometric technologies in an educational setting.  A variety of major biometric technologies will be briefly described.  Options of implementation, dealing with topics such as, smart cards in a K-12 environment, distance learning in higher education, and individual biometrics issues will be discussed.  This assessment is to be presented for educational purposes and will be presented to a fictitious member of congress.  The assignment material is available at the following web address, http://www.bsu.edu/web/jcflowers1/rlo/206taassignsp2004.htm.

Biometric Technologies

    Biometric technologies are defined as "automated methods of identifying or authenticating the identity of a living person based on a physiological or behavioral characteristic" (Bowman, E, 2000).   Automated methods can be broken down into a mechanism used to scan, a processing or comparison unit, and an interface with a variety of application systems.  Identification and authentication are very similar parts with a few precise differences.   Identification refers to when characteristics are selected from a group of stored images, this produces a list of possible or likely matches (Bowman, E, 2000).  Authentication refers to the when an individual makes a claim that he or she is someone specific, and just that one person's characteristics are being checked to see if they match.  Finally, the difference between physiological and behavioral characteristics must be defined.  A physiological characteristic is a physical characteristic that does not change frequently, such as, fingerprint, hand silhouette, iris pattern, or blood vessel pattern on the back of the eye (Bowman, E, 2000).  Behavioral characteristics are more of a reflection on psychological patterns, such as, signature, keystroke analysis, and speech patterns (Bowman, E, 2000).

    A variety of biometric technologies have been around for many years.  Physiological and behavioral characteristics are becoming more and more efficient types of identification everyday.  However, biometrics can be traced back as far as the 14th century in China (Transition Year Students, n.d.).  It is reported that the Chinese merchants stamped the children's feet and hands on paper with ink in order to distinguish them from one another.  In the late 1800's, Alphonse Bertillion wished to fix the problem of identifying criminals and established a specific field of study for biometrics (Chadwick, K, Good, J, et al.,  2001).  Bertillion developed a method of biometrics which consisted of taking measurements of various parts of the body, such as the head, shoulders, fingers, and skull.  This method was named Bertillionage after Bertillion (Chadwick, K, Good, J, et al.,  2001).  This method caught on quickly and spread widely.  However, the downfall to Bertillionage was soon found, two people could have the exact same measurements therefore one person could be charged with the wrong doings of multiple people.

Fingerprint Analysis

    Fingerprint analysis dates back to the 14th century and is still in heavy use today (Chadwick, K, Good, J, et al.,  2001).  Fingerprint analysis has been successfully used in numerous applications.  Everyone is known to have their own unique and immutable fingerprints (Prabhakar, S, & Jain, Anil, n.d.).  Fingerprint matching techniques can be classified in two categories:  minutiae based and correlation based.  Both techniques have their own unique downfalls.  Minutiae points are difficult to extract if the fingerprint scan quality is low.  The correlation based method overcomes the downfalls encountered with the minutiae based technique.  However, it has downfalls of its own that need to be dealt with.  Correlation based techniques require the precise location registration points and are affected by image translation and rotation.  If the finger is rotated even slightly it can throw off the entire scan and cause the fingerprint to be read incorrectly.  A fairly new idea being introduced into fingerprint analysis is the concept of incorporating a scanning device into the mouse of a computer (Secure-It, n.d.).  This can be very helpful in identifying who is using a computer when in an educational setting.  According to Secure-It (2003), the U-Match biometric access mouse allows 100 percent positive user fingerprint verification.

Hand Scan Analysis

    Another method of biometrics involving fingerprint scan is the geometric hand scan analysis.  Some scan devices measure only a few fingers, while others will take the entire hand into account while scanning (findBIOMETRICS.com, n.d.).  Hand scanning is concerned mainly with the physical characteristics of the users fingers and hand (BiometriTech, 2004).  Physical features taken into account include:  finger curvatures, thickness and length, the height and width of the back of the hand, the distances between joints, and the overall bone structure (findBIOMETRICS.com, n.d.).  Internationally, many airports use this technology.  The hand scan can be used in airports to allow frequent flyers to by pass waiting lines and immigration and customs.  Many work settings are now using a type of hand scan technology so that employees can quickly record time and attendance.  This idea could be easily incorporated into the school systems as a method of taking attendance.

Keystroke Dynamics

    A fairly new type of biometrics is typing biometrics or keystroke dynamics.  Keystroke dynamics refers to the analyzing a persons typing methods (BioPassword, 2004).  It has been found that every person types or presses the keys on a keyboard differently.  According to BioPassword (2004), variations can be seen and identified within the following characteristics:  durations of keystrokes, latencies between keystrokes, inter-keystroke times, typing error frequency, and force keystrokes.

Signature Analysis

    Signature analysis, hand writing scans, and dynamic signature verification have all experienced little exposure in the world of biometrics identification technologies (BiometriTech, 2004).  According to BiometriTech (2004), signatures are considered the least ethically challenged and obtrusive form of biometrics.  Handwritten signature analysis can relate to the series of movements, rhythm, acceleration, and pressure flow can contribute to the identification of the persons signature (BiometriTech, 2004).  Signature analysis is thought of as having a quick return of investments.  The previous United States eSign Bill and related legislation that was passed within the past 5 years has opened a window of opportunity for online transactions and pin numbers which have been assigned to a persons signature (BiometriTech, 2004).  This bill extended the legal power of the handwritten signature to the electronic world.

Gait Biometrics

    Gait biometrics identifies a person by the way the walk, run, or any other type of motion of the legs. A person’s gait is the way in which they move on their feet. Gait biometrics can be used to identify everything from the length and thickness of an individuals legs to the stride of their step. Unlike some other, more researched and identifiable methods of biometrics, gait biometric technology faces the difficulty of identifying not only a particular body part but a motion (World Information, 2003).

    At Georgia Tech University, professors and students are developing a system that will be able to recognize a persons gait by radar signals. This Doppler effect is 80- 95 percent effective in identifying an individual (Lemos, R., 2002). Research Engineer Bill Marshall explains that they can decode radio signals reflecting of a person’s walking stride, as they walk toward the signal (Hirshon, B., 2002). This signal pattern is converted to an individuals audio signature, which can be cataloged for later use. Marshall is sure to include that audio signals, decoded from an individual’s gait, are not unique to a particular person. Any given number of people may have the same audio signature, but unlike the unique DNA or finger prints, gait biometrics can catalog an individual without them knowing they were ever being observed (Hirshon, B., 2002).

    Gait biometrics would be particularly beneficial in identifying criminal suspects. Police could scan a large crowd for a suspect without them knowing they were on to them (Lemos, R., 2002). Gait biometrics can also be used to identify shoplifters-particularly ‘pregnant’ women. Women pretending to be pregnant will walk differently then women who are actually pregnant (Hirshon, B., 2002). This would be a large advance in technology if introduced to common retail stores.

    Some sources recognize what gait biometrics says it can do, but doubts it’s ability to perform. A gait system can easily be deceived because walking patterns can be sometimes be altered. Skeptics also doubt gait biometrics ability to perform in real life scenarios, such as airports and large crowds (Ackerman, L.,2003). Regardless of what critics say, gait biometrics will have to prove it’s capabilities in action.

 Dental Biometrics

    Dental biometrics is one way of determining a person’s identity. According to A. K. Jain (2003), dental biometrics is mostly used in identifying the deceased, but is becoming more common for living people.

    Dental biometrics primarily uses X-ray comparison for identification purposes. Although other forms of identification are available, such as teeth impressions and restorations. Currently the Kerr Corporation offers an identification system for children called Toothprints ® . Toothprints ® was developed by a pediatric dentist and uses a thermoplastic wafer that will allow a dentist to record a child’s personal tooth characteristics (21st Century Dental, 2002).

    Just like other biometrics the position of teeth are unique to each person. These Toothprints ® have other qualities to them to they capture saliva which hold the scent of that particular child. This may help with the identification by odor or DNA as well as dental scans (21st Century Dental, 2002).

    Complications such as dental characteristics changing over time can affect the accuracy of dental biometrics. A few characteristics that can change affecting the outcome of dental scans include:  loss of teeth, change color in teeth, or alterations made by a dentist or orthodontist. According to Jain (2003), there are many features that can be compared such as the tooth being present or not, dental work like a cap crown or filling, and general size and shape. (Jain, A. K., 2003).

    Pretty (2001), states that teeth are an appropriate and accurate way of identifying a person. Teeth also give us an opportunity for identification by their longevity. Teeth survive most postmortem events and growth changes. Other forms of biometrics identify physical characteristics and traits that may change more frequently then teeth. Most people have the majority of their permanent teeth by late childhood (Pretty, K. & Sweet, D., 2001).

Voice Biometric

    Voice biometric technology can be used in a variety different environments.  It can be useful in the workplace or phone conversations and conference calls. The most common type of voice biometrics used today is voice activated cell phones (Biometrics, 2002).

    Simply put, voice scanning works by recognizing and individuals unique characteristics and voice patterns in their speech (HTG, 2001). In some systems the software requires a clear break between words, in newer technology an individual can speak at a normal rate. This software needs an initial voice code of an individual to test and match later audio bites to (BioLink, 2000). Voice biometrics works by digitalizing an individual’s speech and creating a number code to match future audio bites with. The movement of glottal tissues, lips, the jaw, and the tongue all effect an individuals voice patterns (Biometrics, 2002).

    Voice recognition technologies are still in the experimental stages, there have been accuracy problems because of the way and individual speaks or the nature of their voice (BioLink, 2000). Other problems in voice recognition technologies are outside factors such as natural sound or loud noises in the background can make the identification process more complicated. Also, individual illness can have an effect on voice patterns, creating an unreliable technology through many situations (HTG, 2001).

    Despite these disadvantages some sources believe voice recognition has the most potential for growth in the years ahead. It only needs a simple microphone and computer software.  It can be used over telephone and for other telecommunications purposes. Voice recognition is already in the works for being integrated into the automotive industry-used for voice controlled audio systems, windows, headlights, turn signals and other remote activities (Baird, S., 2002).

DNA Biometrics

    Deoxyribonucleic acid (DNA) Biometrics could be the most exact form of identifying any given individual (Baird, S., 2002). Every human being has its own individual map for every cell made, and this map, or ‘blueprint’ as it more often is called, can be found in every body cell. Because DNA is the structure that defines who we are physically and intellectually, unless an individual is an identical twin, it is not likely that any other person will have the same exact set of genes (Philipkoski, K., 2004).

    DNA can be collected from any number of sources: blood, hair, finger nails, mouth swabs, blood stains, saliva, straws, and any number of other sources that has been attached to the body at some time. DNA matching has become a popular use in criminal trials, especially in proving rape cases (Landers, E., 1992). The main problems surrounding DNA biometrics is that it is not a quick process to identify someone by their DNA. The process is also a very costly one (Baird, S., 2002).

    DNA Biometrics is not a fool proof method of identification. If forensic scientists to not conduct a DNA test properly, a person’s identification code can be skewed. Another problem is matching prior DNA samples to new samples; this is a bigger problem in DNA fingerprinting. The information looks like a bar code, and if not closely inspected an incorrect match could be made (SAIC, 2004).

 Facial Biometrics

    Facial biometrics is one of the fastest growing areas of biometrics. With growing technologies facial recognition can convert a photograph or a video image into a code that describes a face’s physical characterizes (Baird, S., 2002). This can be used to identify the common person from a distance, without intruding into their personal space.

    Computer software for facial identification reads the peaks and valleys of an individual’s facial features; these peaks and valleys are known as nodal points. There are 80 nodal points in a human face, but the software needs only 15-20 to make an identification. Specialists concentrate on the golden triangle region between the temples and the lips. This area of the face remains the same even if hair and a beard is grown, weight is gained, aging occurs, or glasses are put on (Rutherford, E., 2001). 

    Computers cannot recognize a face as well as humans can sometimes. Government studies have shown facial recognition software has incorrectly matched a face with a photograph taken 18 months ago 43 percent of the time. These studies even used high quality photos, not addressing photos or video with pour lighting or bad angles (ACLU, 2002). This isn’t to say that facial recognition should be ruled out all together, but should not be the sole method of identifying an individual.

    Facial biometrics have been used for surveillance since being developed. Cameras installed at ATM machines have been used to verify users (Rutherford, E., 2001). Facial recognition is used for surveillance in airports, government facilities, and other public places. Facial recognition has also been used in locating criminals, terrorists, and missing children (ACLU, 2002).

Retinal or Iris Scan

    The retinal or iris scan can be defined as the recognition of the person’s iris or retina. The person approach a reading device and it scans the person’s eye to decide the correct identity. Like the fingerprint, it is assumed to be unique for each person and each eye, even for twins (Khader, A. T., Poh, N., et al., n.d.). Over time, scientists have shown that the error rate for the retinal or iris scans are extremely low and do not leave much room for error. Iris scanning was pioneered by [Daugman, 1995] (Khader, A. T., Poh, N., et al., n.d.). This scan is also quite popular and on the rise due to its incredible speed ability to read a person’s eye.

     The iris scan is becoming a more used scan due to its ability for the person’s eye to be scanned without having to directly come into contact with the equipment. The retinal scan can be taken from a foot away from the device.

 Ear Scan

     Every person has a differently shaped ear. The ear is very unique to each individual person just like a fingerprint. A possible device that would measure the ear shape would be installed on the common telephone. Although this technique is gaining recognition the possibility of people wearing ear-muffs is causing major problems with this scanning operation (Bunham, R., n.d.). This operation is just done by a laser scanning the ear and recognizing the distinct shape for that particular person.

 Smart Card

     Smart cards are an excellent and useful tool to use in biometrics technology. They can combine face-scan, fingerprint, and card swipe identification all into one device. In 1992 Polaroid issued the largest biometrically secure ID card system in the world for Mexican voters (Ward. N., n.d.). To date more than eighty million Mexican voters have smart cards. Smart cards are the way to go in many people’s eyes. They combine multiple biometric possibilities into one which leaves less room for error which is extremely critical. Room for error is minimized.  Error rate is a critical item to be considered when a persons identification is at stake.     

 Option # 1

Implementing Biometric Technologies into Distance Learning

Author: Erica Frazier

    Distance learning education has been around for many years, it's use is dated back at least 100 years (Galusha, J. M., n.d.)  Although distance education has evolved a considerable amount over the past 100 years, there are still many similar issues arising with the process.  Technology has changed what was once thought of as distance education; through computers, cable lines, satellites, and many other technologies, it is now possible to have a sort of face to face communication although the group of people may be many miles apart.  Many issues still stand even with these advanced technologies.  The following issues will be addressed: How do we effectively identify a person or persons during certification sessions, homework, and general correspondence?  Who will we implement these technologies upon?  How cost effective will these technologies be?  It is proposed that a variety of biometric technologies be implemented into the distance learning environment to ensure credibility.

    A major issue the distance learning educational environment is faced with is, how to effectively identify a student whom the teacher cannot visibly see.  A variety of biometric technologies are proposed solutions to this problem.  A new technology available is a computer mouse which has a fingerprint scanning device built directly into it.  The mouse with a finger scanning device directly built into it is a considerable amount cheaper than an attachable finger scan device.  According to Secure-It (n.d.), a package can be purchased including the mouse with a scanning device, documentation, applications, and software can be purchased for $119.00.  According to Karen Thomas (n.d.), a similar device being implementing into schools at the K-12 level for the use fingerprint scanning as a meal card, attendance, and renting of books is costing the school systems $900.00 per scanning machine and $4,000 to $5,000 for all of the hardware and software.  The mouse option is a considerably cheaper option to implement, defeating the thoughts of David Noble as reported by Mark Pescatore (2004), "It's [distance learning] a degraded form of education, it's very expensive..."

    This option, however, creates an issue in itself.  Many students involved in distance learning are using their personal computers at home or in their business office, so how do you choose a group of people who wish to spend the extra money the mouse and software?  It is assumed that along with intending implementation of this technology, there will be grant money assigned to the participating schools so they can purchase the software and require the students to install it onto the computer in which they will be using for class work.  If grant money is not available, the fee for this biometric technology should be included in the schools technology fee.  It is very important that this technology be implemented in order for distance learning to gain credibility along with normal formal education (Galusha, J. M., n.d.).

    A special subcommittee of congress should be organized, consisting of business associates, teachers from the K-12 level, teachers from the post-secondary level, current and past distance learning participants, and administrators, that will focus on the design and implementation of biometric identification in the distance learning environment.  This committee will be in charge of deciding how much money will be allotted for the technology, which technology will be most effective, which schools will have the option of testing the technology, and any other issues that may arise during the implementation of the chosen technology.  This group will also be in charge of setting the mark for what is considered successful in the trial and if further implementation should be considered.

    Special considerations will be made concerning who is the selected target group for this test.  The subcommittee will have guidelines which they must go by.  These guidelines should include, but not be limited to, the following:

With these guidelines and other selected guidelines in mind, the test group should be chosen.  The group should involve enough variance in mental and physical capabilities to fully identify problems with this system.  After successful implementation at the higher education level, the next step may be to test this method with in the K-12 school systems.

    The software for this technology would have to be modified to effectively identify the user throughout the coursework.  The original design of the mouse with a fingerprint scanner was focused on identifying a user so that files and other secure documents could not be accessed by others (Secure-It, n.d.).  In order to fully ensure the person completing the work is the person who they say they are, scanning would have to take place several times throughout the course of the assignment or test.  The scanning would also have to take place when the finger is actually on the mouse.  A way to successfully check several times would be to set up to system so that every time the mouse button was depressed, scanning would take place.  In order to ensure the mouse button would actually be depressed numerous times, some tests would have to be modified.  In a variety of tests now, it is possible to go the majority of the way through a test without ever actually hitting the mouse button (by the use of the Tab key).  The tests would each have to be modified so the mouse buttons were required to complete the task.

    According to Secure-It (n.d.), their version of the mouse with a scanning device, the U-Match Mouse ®, allows for 100 percent verification.  The following chart identifies the specifications of this technology:

PRODUCT SPECIFICATIONS

    Eye Net Watch (2001)

    If this technology is successfully implemented into the distance learning environment at the collegiate level, it could lead to a better accredited distance learning curriculum.  The mouse with a scanning system could fully ensure who was completing the work therefore leaving no room for debate.

Option # 2

Biometric Issues

Author:  Scott Greiner

A proposed policy for using biometrics as an identification and security system in our schools strives to function as a tool to prevent disruptive privacy invasion. Biometrics is only one of many technological solutions to identification and security. These intrusive solutions for education are unnecessary actions. A certain respect and consideration should be given to our students.

Currently schools are becoming more cautious of security measures and will need new forms of identification as they move forward in a new time of national concern for security. Biometrics is not the best way to attain the necessary identification of an individual. According to the National Education Association (2004), NEA, there are many other ways to keep the security in our school appropriate, such as guards, counseling, conflict-resolution programs and better communications between school and home. Also, identification is possible with out biometrics. Identification cards, identification numbers, and passwords have proved to become a fairly reliable practice and success. Leave the biometrics, an intrusion and an invasion of privacy, to places that can afford these distractions.

Biometrics carries with it a large support group. These groups state many reasons for installing different forms of biometrics into our schools. Although biometrics demonstrates it can be a useful tool in the identification process, there are negative aspects of this process. BIO-key International (Find Biometrics 2003) states that schools use their product because they are continually looking for ways to save money so that so that more funds can be directed toward the education process. This goal is great and should be applauded but does biometrics in schools really help in accomplishing this goal? Claudia Graziano (2003) states that the cost of a finger print biometric system being implemented in a school costs about $5,000. This is not an outrageous amount of money, but Chris Hoofnagle (2002) brings up the fact that every biometric system needs a reliable backup. For example, students at Penn Cambria, who would did not want to take part in the finger print system, were allowed to keep and use their ID cards (Graziano 2003). Not only would a school have to install, maintain, and integrate a new biometrics system, but they would also have to keep their current form of identification or switch to another (other than biometrics). Biometrics creates a waste of resources having to keep the current form and implement another. Maintaining current identification processes retains more money, time, and labor than beginning a new biometrics system of identification.

 Recognition Systems Inc. (Find Biometrics n.d.)  establishes the probability of a biometric system allowing someone to get falsely approved at a hand reader at 0.1%. The false rejection rate of a biometric system is slightly higher around 1%. Recognition Systems state a problem will happen about two times a week if they use the reader 400 times a day. The two failures of every 400 take time and effort to fix. Imagine a school of 3,000 students who get there finger print scanned at the beginning of each period of the day. An eight period school day would have a total of 24,000 scans a day with around 120 errors per day. That would take just as much time to correct this problem as it would to orally take role. These problems consist only of their own internal problems and do not address the fact that as a security measure, there will be people who will try to bypass them by using any known method. This company also fails to make available the reprogramming needs of such a system based bodily changes.

There are easily found and easily carried out methods of bypassing a biometric system. Hoofnagle (2002) states that many of these print systems can be fooled as simply as blowing on the read surface of scanner to condense the oils of the pervious person. This seems to be a simple way to get around a complex system. Tsutomu Matsumoto (Schneier, 2002) concluded that with as little as $10 dollars and some time, a scanner could be fooled. Matsumoto made a gelatin mold of a finger and used it to bypass a scanner system. This process was accepted by the scanner around 80 percent of the time. Matsumoto also discovered he could fool a scanner with finger prints left on surfaces such as glass. He enhances the print with an adhesive then photographs it. After he digitally enhances the finger print, he prints it, and etches it onto a piece of copper making it 3-D. Matsumoto then  makes a gelatin print using the etched copper. This fake print will also pass as a particular person around 80 percent of the time. Matsumoto successfully bypassed 11 of 11 biometric print systems using this process. These systems are to easily manipulated to be trusted in securing our students. If an individual was determined enough to spend some time, who knows what could happen. If a teacher knows the difference in voice, it is just as easy, and more effective, to take role in each class then to have students stand in line to have there print scanned.

            There are many forms of biometrics not just finger print or hand scanners that could be used in schools. Face recognition is another possibility. According to Michelle Rushlo (2003) a Phoenix school has installed a face scan system. These scanners will scan people entering through the main entrance and the school’s office. This will be used to detect supposable sex offenders, missing children, and alleged abductors. Although there is many positive intents and praise about this method, this biometric system again can be fooled. Lim Dong-hun (n.d.) says that these systems are favored because of the limit of interaction of the technology and the person. Lim Dong-hun (n.d.) also brings up the many failures of system like this. These failures extend from not being able to distinguish between twins, not identifying a person after a haircut, and not recognizing someone after removing their glasses or putting them on. Even Rushlo (2003) goes into issues on this system such as lighting changes and facial expression can disrupt the effectiveness of this technology. The biggest problem seen here is there already has to be a picture of this person in the database, so if this is a first offence what good will it do.

Stephen L. Baird (2002) states that “Iris scanning is a non-intrusive, extremely accurate method that can be used for identification.” Linda Ackerman (2003) acknowledges that the iris scanners scan around 266 characteristics more then any other biometric and the characteristics don’t change over the years. Ackerman (2003) does have problems with such systems, for example, these scanners require you to stare into a camera. This would not be appropriate in a school or save time. Each student checking in or out with this scanner would take forever and younger students would have to be monitored. Even if this system was only for security there would be problems. Ackerman states that any lighting condition change could vary results and again that person’s iris scan would have to have been previously recorded. Iris scanners do not carry with them a zero error rate either so basic malfunctions could allow anything to happen. This system has also been fooled before by a German group. As for saving money and human resources to allocate more to students, iris scanning is the most expensive form of a biometric.

            Voice recognition is another form of biometrics possible for schools. Voice verification has not had the backing that other systems have had for being initiated into our schools. Simson Garfinkel (2000) lived with a voice print lock on his house. This lock required him to speak a pass-phrase to enter his home. During his time with this system he noticed some inconsistencies. One instance is that he could not get the system to work right if there was some background noise. This would consist of storms, traffic, and people. Also he noticed that many times some people would be recognized on their first try while others need to speak multiple to be allowed in. For this reason he had to give codes that could be entered if the voice command did not work. Many other places also use this idea of an alternate code for example the University of Georgia uses the social security number (SSN) according to Hoofnagle (2002). All some one needs to do is take a person’s SSN enter it in to one of the scanners scan their hand and they now believe that print goes with that name. This totally defeats the purpose of having a system like this. Imagine a school that has many children trying to have them speak and be recognized without having background noise interfere with the reader (Garfinkle 2002).

Ideas for biometric systems such as odor, DNA, dental, ear scan, and gait all have many moral issues involved with them. These types of biometrics require us to know more then we should about any human. These ideas all sound like a way for Total Information Awareness (TIA) to become prevalent. Erich G. Lukas (n.d.) explains TIA as a computer system run by the department of defense that will track your every move. TIA will know when you make a purchase to where you are walking by gait identification via a satellite. This goes into breaking laws of privacy of each student and people in the United States. American Civil Liberties Union (2003) points out that TIA record personal information consistently which means that TIA takes all personal privacy. This program being initiated would mean that current privacy laws need to be changed to be more lenient. American Civil Liberties Union (2003) should be listened to when they say “Congress should not allow the Defense Department to develop unilaterally a surveillance tool that would invade the privacy of innocent people inside the United States (Hunter 2003).” The chart below shows that these forms of biometrics are not worth the costs and many have a poor comfort level.

green = best red = worst

Figure 1 http://www.bromba.com/faq/biofaqe.htm#Merkmale

Keystroke and signature are two other forms of biometrics. Viewing Figure 1, keystroke ranked lower then password in every case besides cost, where they tied. This demonstrates that switching to a system that is less reliable would not be the best step. Cooper Advanced Technology (2003) points out a few problems with the keystroke analysis that very commonly would happen in schools. They point out that keystroke identification measures a rhythm; because these rhythms change with learning, fatigue, and distraction this is an inconsistent measure of an individual. Signature functions the same way, recording speed, pressure, and location which constantly change (FSU Introductory Textile Science, 2003). Both of these biometric system require that patterns remain unchanged and in a facility that teaches and promotes improving writing and typing this would seem contradictive.

Smart cards can work in schools just as much as regular ID cards. If smart cards are implemented they carry the same problems that ID cards do. Smart cards can be used to check into every class like a punch clock at the workplace. Senpass (2001) states that using a card for attendance is not new, although the technologies behind smart cards are. The problem that evolves is the same as in any form of identification-who is to say one student does not give another student their card to check them in. For security purposes a card could be lost or stolen and then infiltration could be accomplished. Even if a password would be needed along with the card this could be a problem. This system like other systems could not be a stand alone system and should not be considered in school

It all comes down to there is no replacing the teacher-student contact. Currently teachers are pushing themselves further and further from our students. This is just another way for teachers to pay less attention. Carlos A. Soto (2002) states that “bad biometric security is worse than no security at all (Soto 2002).” If a biometrics system fails, it isn’t just a traditional identification method failing, it is money and time failing at the expense of people’s privacy. There is not a single biometric system that can compete with human recognition. Therefore, the recommendation for Congress is that no biometrics identification methods should be approved for funding or implementation. Legislation should be proposed to ban biometrics from entering any school that receives federal funding.

 Option # 3

Smart Card Use in High Schools: Is this a secure situation?

Conclusion

    Each of these three policies gives an in-depth look into biometrics in different forms in education. Each one was researched thoroughly trying to determine how  biometrics would benefit an educational setting. Each biometric system offers positives and negatives to the school setting and each policy brought to light a different form of biometrics. If there is any more information needed or any questions please feel free to contact any author.

References

21st Century Dental (2002).  Toothprints ®. Retrieved April 24,
     2004 from ,  Web site:
     http://www.21stcenturydental.com/smith/Toothprints.htm

Ackerman, L. (2003). Biometrics and Airport Security. Retrieved April 25, 2004 from  
     http://www.privacyactivism.org/Item/64

Baird, S. L. (2002). Biometrics:  Security Technology. The Technology
     Teacher, 61 (5), 18-22.

BiometriTech (2004, February).  Signature Verification Biometrics
     Market to Overcome the Effect of Reduced IT Expenditures.
     Retrieved April 20, 2004 from ,  Web site:
     http://www.tmcnet.com/usubmit/2004/Feb/1024039.htm

Biometrics (2002).  Identification and Verification. Retrieved
     April 23, 2004 from ,  Web site:
     http://rpmfeeler.no-ip.com:8080/duncan21/biometrics/voice.html

BioLink (2000).  Understanding Voice Recognition. Retrieved April
     23, 2004 from ,  Web site:
     http://www.findbiometrics.com/Pages/voice%20articles/voice_1.html

BioPassword (2004).  Biometrics. Retrieved April 19, 2004 from ,
      Web site:
     http://www.biopassword.com/home/technology/biometrics.asp

Bowman, E. (2000, January).  Everything You Need to Know About
     Biometrics. Retrieved April 2, 2004 from Indentix Corporation,
      Web site: http://www.ibia.org/EverythingAboutBiometrics.PDF

Bunham, R. (n.d.).  The Eyes Have It. Retrieved April 22, 2004
     from ,  Web site: http://www.cfoasia.com/archives/200210-04.htm

Chadwick, K, Good, J, et al.  (2001).  History of Biometrics.
     Retrieved April 18, 2004 from ,  Web site:
     http://ntrg.cs.tcd.ie/undergrad/4ba2.02/biometrics/history.html

Cooper Advanced Technologies, Inc. (2003). Biometrics. Retrieved April 25, 2004 from
      http://www.catech.com/biometrics.htm

Dong-hun, L. (n.d.). Biometrics as a New Technology. Retrieved April 25, 2004 from
      http://maincc.hufs.ac.kr/~argus/no343/t_c2.htm

Eye Net Watch (2001).  Biolink U Match Mouse 2.5 (USB) .
     Retrieved April 24, 2004 from ,  Web site:
     http://www.eyenetwatch.com/biosecurity/biolink-usb-fingerprint-mouse.htm

Find Biometrics (2003). BIO-key Scores Straight A’s in Education Application.
      Retrieved April 25, 2004 from http://www.findbiometrics.com/viewnews.php?id=512

 Find Biometrics (n.d.). Convenience vs. Security: How Well Do Biometrics Work?
     Retrieved April 25, 2004 from http://www.findbiometrics.com/Pages/guide2.html

findBIOMETRICS.com (n.d.).  Understanding Hand Scanning.
     Retrieved April 12, 2004 from ,  Web site:
     http://www.findbiometrics.com/Pages/hand_finger%20articles/hand_1.html 

 FSU Introductory Textile Science (2003) Biometrics: The touch, the Scan,
     the Pattern of Our Lives. Retrieved April 25, 2004
     from http://cte1401-01.sp00.fsu.edu/holly.html

Galusha, J. M. (n.d.).  Barriers to Learning in Distance
     Education. Retrieved April 24, 2004 from University of Southern
     Mississippi,  Web site: http://www.infrastructure.com/barriers.htm

 Garfinkel, S. (2000). Database Nation. Retrieved April 25, 2004 from
      http://www.acm.org/ubiquity/book/s_garfinkel_1.html

Graziano, C. (2003). Learning to Live with Biometrics.
     Retrieved April 25, 2004 from
      http://www.wired.com/news/privacy/0%2C1848%2C60342%2C00.html

Hirshon, B (2002).  Gait Recognition. Retrieved April 23, 2004
     from ,  Web site:
     http://www.sciencenetlinks.com/sci_update.cfm?DocID=149

Hoofnagle (2002). Six Recommendations to Create A More
     Privacy-Sensitive College or University.
     Retrieved April 25, 2004 from http://www.epic.org/epic/staff/hoofnagle/studentprivacy.html

HTG Advance Systems (2001).  Voice Scanning. Retrieved April 23,
     2004 from ,  Web site:
     http://www.htgadvancesystems.com/advance/biometrics/speech/

 Hunter, D. (2003). Letter Opposing TIA. Retrieved April 25, 2004 from
      http://www.eff.org/Privacy/TIA/duncan-hunter-letter.php

 Lukas, E. G. (n.d.). Will Americans Become WWII Germans. Retrieved April 25, 2004 from
      http://www.patriotist.com/miscarch/el20030113.htm

 National Education Association (2004). School Safety. Retrieved April 25, 2004 from
      http://www.nea.org/issues/safescho/

Philipkoski, K. (2004).  Is That Really You:  Check my DNA.
     Retrieved April 23, 2004 from ,  Web site:
     http://www.wired.com/news/medtech/0,1286,56696,00.html

 
Prabhakar, S, & Jain, Anil (n.d.).  Fingerprint Identification.
     Retrieved April 12, 2004 from Michigan State University,  Web site:
     http://biometrics.cse.msu.edu/fingerprint.html

Pescatore, M. J. (2004).  Diploma Mill Mentality: Distance Learning
     Can't Take the "Easy" Way Out. Retrieved April 23, 2004 from ,
      Web site: http://www.governmentvideo.com/2002/08/video_0802.shtml

 Rushlo, M. (2003). Phoenix installs face scanners in school. Retrieved April 25, 2004 from
    http://www.boston.com/news/nation/articles/2003/12/15/phoenix_installs_face_scanners_in_school/

Rutherford E. (2001).  Facial Recognition Technology has People
     Pegged. Retrieved April 23, 2004 from ,  Web site:
     http://www.cnn.com/2001/TECH/ptech/07/17/face.time.idg/

SAIC (2004).  Aiding DNA Identification on the Missing. Retrieved
     April 23, 2004 from ,  Web site:
     http://www.saic.com/cover-archive/law/codis-dna-profiling.html

Schneier, B. (2002). Crypto-Gram Newsletters. Retrieved April 25, 2004 from
      http://www.schneier.com/crypto-gram-0205.html).

Secure-It (2003).  Biometric Authentication. Retrieved April 12,
     2004 from ,  Web site: http://www.secure-it.com/products/umatch/

SenPass (2001). Market Focus. Retrieved April 25, 2004 from
      http://www.senpass.com/market_focus.htm

Smith, G. (n.d.).  Biometric ID's: Hand Scan or Geometry.
     Retrieved April 20, 2004 from ,  Web site:
     http://www.biometricid.org/hand.html

Smith, G. (n.d.).  Biometric ID's: Signature Scan.
     Retrieved April 20, 2004 from ,  Web site:
     http://www.biometricid.org/signature.html

Soto, C. A. (2002). Biometric security not ready to replace passwords.
     Retrieved April 25, 2004 from http://www.computeruser.com/news/02/05/04/news4.html

The American Civil Liberties Union (ACLU) (2002).  Q & A on Facial
     Recognition. Retrieved April 23, 2004 from ,  Web site:
     http://archive.aclu.org/issues/privacy/facial_recognition_faq.html

Thomas, K. (2002).  Finger Scans Let Kids Touch and Go. Retrieved
     April 25, 2004 from ,  Web site:
     http://www.usatoday.com/tech/news/2001-02-06-fingerscans.htm

Transition Year Students of Vocational School Athenry Co. Galway
      (n.d.).  A Brief History of Biometrics. Retrieved April 20,
     2004 from ,  Web site:
     http://www.galwayeducationcentre.ie/athenry/a_brief_history_of_biometrics.htm

Ward, N. (n.d.).  Smart Card Biometrics. Retrieved April 22, 2004
     from ,  Web site:
     http://www.copybook.com/publications/article.asp?artID=329&pubID=2